Triple
T32561842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1984 New York City subway shooting |
E832247
|
entity |
| Predicate | occursOnTrain |
P62786
|
FINISHED |
| Object | Number 2 train |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Number 2 train | Statement: [1984 New York City subway shooting, occursOnTrain, Number 2 train]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occursOnTrain Context triple: [1984 New York City subway shooting, occursOnTrain, Number 2 train]
-
A.
trainsOn
Indicates that one entity receives training, instruction, or practice using or based on another entity (such as a resource, dataset, tool, or subject).
-
B.
isOnRailway
chosen
Indicates that one entity is positioned on, aligned with, or traveling along a railway track or railway system in relation to another entity.
-
C.
servedByNamedTrain
Indicates that a service, route, or journey is operated specifically by a train with a particular designated name.
-
D.
occursDuringJourneyTo
Indicates that an event or action takes place while a journey to a specified destination is in progress.
-
E.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:03 a.m.